dev.to/tuomo_pisama/the-17-ways-ai-agents-break-in-production-2c1
archives
This URL has 1 public saves. The first save was Apr 2, 2026, 04:31 PM and the latest save was Apr 2, 2026, 04:31 PM.
View recent saves on this domain
Latest saved version
The 17 Ways AI Agents Break in Production - DEV Community
This is the newest public snapshot for this URL and the best place to start reviewing the page.
Source URL
https://dev.to/tuomo_pisama/the-17-ways-ai-agents-break-in-production-2c1
About this page
This page discusses 17 distinct failure modes of AI agents in production environments. Unlike traditional software, AI agents fail through drifting, looping, hallucinations, and silently producing incorrect results while monitoring systems appear normal. After analyzing 7,212 agent traces from 13 external sources, researchers catalogued consistent failure patterns across LangGraph, CrewAI, AutoGen, n8n, and Dify deployments. Each failure mode includes a definition, production example, severity level, and detection method. The first example, Infinite Loops, describes agents stuck repeating the same actions without progress, causing significant API costs ($800+) while appearing successful individually.
Saved versions
dev.to/tuomo_pisama/the-17-ways-ai-agents-break-in-production-2c1 web archives are listed here. You can still review the saved screenshot and HTML even if the original page disappears.